Hannum · Molecular cell 2013 · cross-sectional observational biomarker modeling study · n=656

Genome-wide methylation profiles reveal quantitative views of human aging rates.

Cited 4617 times in the scientific literature.

Level 4 - case-series / case-control

Cross-sectional epigenetic biomarker modeling study in human tissue samples.

PubMed 23177740 · doi:10.1016/j.molcel.2012.10.016 · record verified 2026-08-30

What was done

Authors built a quantitative model of human aging using DNA methylation profiling across more than 450,000 CpG markers from whole blood samples of 656 human individuals aged 19 to 101. They evaluated the model's ability to measure individual methylome aging rates and tested associations with sex, genetic variants, gene expression (transcriptome), non-blood tissues, and tumor tissue.

What was found

The whole-blood methylation model measured human methylome aging rates across the age span of 19 to 101 years. Methylome aging rates were influenced by sex and genetic variants, correlated with epigenetic drift and transcriptomic changes, generalized to other human tissues, and revealed accelerated aging in tumor tissue. The abstract reports no numerical metrics, correlation coefficients, or effect sizes.

Why it matters

This study introduced one of the foundational genome-wide epigenetic clocks, showing that DNA methylation patterns provide a quantitative readout of biological aging rates and tissue-specific age acceleration.

Limits

The abstract reports no numerical performance metrics (such as error rates or correlation with chronological age) or effect sizes. The primary model was developed on cross-sectional data rather than longitudinal follow-up, and the health status or demographic details of the 656 individuals are not specified in the abstract.

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